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multi algorithm » mould algorithm (Expand Search), auction algorithm (Expand Search)
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multi algorithm » mould algorithm (Expand Search), auction algorithm (Expand Search)
5a algorithm » rd algorithm (Expand Search), jaya algorithm (Expand Search), _ algorithms (Expand Search)
complement » implement (Expand Search), complementary (Expand Search)
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…The clique partitioning problem has important applications in many areas including VLSI design automation, scheduling, and resources allocation. In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …”
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A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs†
Published 2010“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …”
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Meta-Heuristic Procedures for the Multi-Resource Leveling Problem with Activity Splitting
Published 2011Get full text
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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization
Published 2024“…This paper presents a novel hybrid optimization method to solve the resource allocation problem for multi-target multi-sensor tracking of drones. This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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Deep Reinforcement Learning for Resource Constrained HLS Scheduling
Published 2022“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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Developing a Cooperative Behavior for Multi Agents System Application to Robot Soccer
Published 2007Get full text
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Fixed set search applied to the multi-objective minimum weighted vertex cover problem
Published 2022“…One important characteristic of the proposed GRASP is that it avoids the use of weighted sums of objective functions in the local search and the greedy algorithm. In the second stage, the bi-objective GRASP is extended to the FSS by adding a learning mechanism adapted to multi-objective problems. …”
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Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes
Published 2025“…Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …”
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Assessment of Inventory and Transportation Collaboration in a Logistics Marketplace
Published 2020Get full text
doctoralThesis -
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Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations
Published 2025“…A comparative evaluation of three FL algorithms (FedAvg, FedProx, Mime-lite) identifies the most suitable aggregation strategy. …”
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Prediction of EV Charging Behavior Using Machine Learning
Published 2021“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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Multi-UAV-Enabled Mobile Edge Computing IoT Systems: Joint Association and Resource Allocation Framework
Published 2024Get full text
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YOLO-DefXpert: An Advanced Defect Detection on PCB Surfaces Using Improved YOLOv11 Algorithm
Published 2025“…Second, the standard convolutional operations are replaced with Deformable Convolutional Networksv2 (DCNv2) in the neck section to improve robustness in identifying multi-scale defects. …”
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A Framework for Predictive Modeling in Sustainable Projects
Published 2012Get full text
doctoralThesis -
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Defense against adversarial attacks: robust and efficient compressed optimized neural networks
Published 2024“…First, introducing a pioneering batch-cumulative approach, the exponential particle swarm optimization (ExPSO) algorithm was developed for meticulous parameter fine-tuning within each batch. …”
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Stability improvement of the PSS-connected power system network with ensemble machine learning tool
Published 2022“…The backtracking search algorithm (BSA) based proposed ensemble model is formed by combining three machine learning (ML) techniques, namely the extreme learning machine (ELM), neurogenetic (NG) system, and multi-gene genetic programming (MGGP). …”
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Machine Learning-Based Approach for EV Charging Behavior
Published 2021Get full text
doctoralThesis